In the operation of receivers, as part of a data transmission system (DTS), it can be desirable to incorporate optimization procedures that modify certain parameters of the receiver.
One approach, is to adjust receiver parameters according to a cost function that measures some type of error. Example cost functions are minimum energy or min-max. Such cost functions can be shown to be effective with respect to a particular type of statistical noise model and a given set of environmental conditions. However, in “real world” situations, involving actual DTS equipment, noise disturbances can come from multiple types of sources, with each source having very different characteristics. Within a single piece of DTS equipment, that serves multiple data links, noise characteristics can vary widely across the links. Also, the noise characteristics of a single link, within a multi-link piece of DTS equipment, can vary based upon whether adjacent links (or channels) are operational. Thus, selecting a particular cost function, by which to optimize the parameters of a piece of DTS equipment, does not necessarily yield, on a consistent basis, the best improvement in a receiver's bit error rate.
Another approach is to minimize a cost function based on the bit error rate itself. However, this type of cost function cannot usually be expressed in a closed form that would make it tractable.
Thus, there is a need to develop optimization techniques, for adjusting parameters of receivers, that operate, across varying noise and environmental characteristics, with more uniform effectiveness.